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Research Papers: Micro/Nanoscale Heat Transfer

Selecting Optimal Parallel Microchannel Configuration(s) for Active Hot Spot Mitigation of Multicore Microprocessors in Real Time

[+] Author and Article Information
Lakshmi Sirisha Maganti

Department of Mechanical Engineering,
Indian Institute of Technology Madras,
Chennai 600036, India
e-mail: lakshmisirisha.maganti@gmail.com

Purbarun Dhar

Department of Mechanical Engineering,
Indian Institute of Technology Ropar,
Rupnagar 140001, India
e-mail: purbarun@iitrpr.ac.in

T. Sundararajan

Department of Mechanical Engineering,
Indian Institute of Technology Madras,
Chennai 600036, India
e-mail: tsundar@iitm.ac.in

Sarit K. Das

Department of Mechanical Engineering,
Indian Institute of Technology Madras,
Chennai 600036, India;
Department of Mechanical Engineering,
Indian Institute of Technology Ropar,
Rupnagar 140001, India
e-mail: skdas@iitrpr.ac.in

1Corresponding authors.

Manuscript received July 6, 2016; final manuscript received April 27, 2017; published online May 23, 2017. Editor: Portonovo S. Ayyaswamy.

J. Heat Transfer 139(10), 102401 (May 23, 2017) (11 pages) Paper No: HT-16-1443; doi: 10.1115/1.4036643 History: Received July 06, 2016; Revised April 27, 2017

Design of effective microcooling systems to address the challenges of ever increasing heat flux from microdevices requires deep examination of real-time problems and has been tackled in depth. The most common (and apparently misleading) assumption while designing microcooling systems is that the heat flux generated by the device is uniform, but the reality is far from this. Detailed simulations have been performed by considering nonuniform heat load employing the configurations U, I, and Z for parallel microchannel systems with water and nanofluids as the coolants. An Intel® Core i7-4770 3.40 GHz quad core processor has been mimicked using heat load data retrieved from a real microprocessor with nonuniform core activity. This study clearly demonstrates that there is a nonuniform thermal load induced temperature maldistribution along with the already existent flow maldistribution induced temperature maldistribution. The suitable configuration(s) for maximum possible overall heat removal for a hot zone while maximizing the uniformity of cooling have been tabulated. An Eulerian–Lagrangian model of the nanofluids shows that such “smart” coolants not only reduce the hot spot core temperature but also the hot spot core region and thermal slip mechanisms of Brownian diffusion and thermophoresis are at the crux of this. The present work conclusively shows that high flow maldistribution leads to high thermal maldistribution, as the common prevalent notion is no longer valid and existing maldistribution can be effectively utilized to tackle specific hot spot location, making the present study important to the field.

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References

Figures

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Fig. 1

Exploded view of the computational domain and arrangement of heaters to mimic a real-time microprocessor and its nonuniform heat release. The arrangement of components of the microprocessor (for a quad core Intel Nehalem® generation 1 architecture), such as the computational core, the cache memory, and I/O bus, has been shown on the microprocessor.

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Fig. 2

Effects of nonuniform thermal load on the performance of PMCS (active heater at 10 W and rest at 2.5 W, as mapped from a real-time microprocessor): (a) U configuration, (b) I configuration, and (c) Z configuration

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Fig. 3

Representation of temperature patterns and hot spot locations for both uniform and nonuniform thermal loads (single heater) in U configuration. The dotted circle represents the peak load heater position.

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Fig. 4

Representation of temperature patterns and hot spot locations for both uniform and nonuniform thermal loads (single heater) in I configuration. The dotted circle represents the peak load heater position.

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Fig. 5

Representation of temperature patterns and hot spot locations for both uniform and nonuniform thermal loads (single heater) in Z configuration. The dotted circle represents the peak load heater position.

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Fig. 6

Comparison of thermal performance of water and alumina–water (5 vol %) nanofluids as heat transfer fluids in parallel microchannel cooling systems under nonuniform thermal load: (a) U configuration, (b) I configuration, and (c) Z configuration

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Fig. 7

Proposed flow configuration(s) for thermal safety of device based on location of active heat source (single active heater). The values represent the corresponding figure of merit. The hot spot locations shown in the first column correspond to the flow direction as shown in the table heading.

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Fig. 8

Figure of Merit of each configuration for known working parameters

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Fig. 9

Effect of nonuniform thermal load on thermal performance of water and alumina–water based PMCS when two heaters (simulating a real processor physical core) are active: (a) U configuration, (b) I configuration, and (c) Z configuration

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Fig. 10

Proposed cooling configurations depending on location of active heat sources (two active heaters) mimicking the physical core of an Intel® Core i7-4770 3.40 GHz processor

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Fig. 11

Thermal contours of U configuration using water and nanofluids as working fluids: (a) and (a1) when H5 heater is active and (b) and (b1) when H7 heater is active. The reduction in temperature as well as hot spot size is markedly visible. (c) Percentage reduction in hot spot core size using nanofluids with respect to water as working fluids.

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